Our paper "Decentralized electric vehicle charging enables large-scale photovoltaics integration in tropical cities" has been accepted for publication in Nature Communications.
Our lab just published a new arXiv paper: Targeted cooling of urban cycling networks for heat-resilient mobility.
Prof. Markus Schläpfer gives a keynote at the UrbanSys2025 meeting, which is part of this year's Conference on Complex Systems (CCS2025) at the University of Siena in Italy (details).
Our lab just published two new arXiv papers on deep learning for mobility flows in cities: 'UrbanPulse' uses graph and transformer models for highly fine-grained predictions across cities. 'FloGAN' uses conditional GANs to generate scenario-based mobility networks.
Markus Schläpfer participates in a workshop at the Complexity Science Hub Vienna to discuss how complexity science has transformed urban thinking.
Hot off the press: Our latest work on using mobile data traffic to reveal the space-use efficiency of cities.
For a study that reveals how gaps in mobility infrastructure impact carbon emissions in countries of the Global South, USE-Lab researchers have won the Best Poster Award at this year's NetMob 2024 Data Challenge.
For an innovative insight into using mobile phone data to estimate charging demands of electric vehicles (EV) and their impacts on the power grid, USE-Lab researchers have won the Best Application Paper Award at this year's IEEE Intelligent Transportation Conference.
Prof. Markus Schläpfer gives an invited talk at this year's ICORS meets DSSV conference ('International Conference on Robust Statistics' / 'Data Science, Statistics, and Visualization') at George Mason University (details).
Prof. Markus Schläpfer gives an invited talk at NYU's Center for Urban Science + Progress (CUSP) on how to leverage urban science for sustainable urban systems engineering (details).
Prof. Markus Schläpfer participated in an international workshop at NYU Abu Dhabi, entitled The Gulf Environment: Understanding and Managing the Challenges.
For an innovative insight into using mobile phone data to increase the efficiency of the existing building stock in cities, a team of researchers from the Urban Systems Engineering Lab has won the runner-up award in the NetMob 2023 Data Challenge.
Our latest work on the potential of deep learning for predicting people flows in cities is out in Transportation.
We welcome Yuehan Yang as a new Ph.D. student. Yuehan is joining us from ETH Zurich and will work on the intersection of urban spatial structure and infrastructure efficiency.